Changes in the ground surface temperature in permafrost regions along the Qinghai-Tibet engineering corridor from 1900 to 2014: A modified assessment of CMIP6

被引:9
|
作者
Xing, Zan -Pin [1 ,2 ]
Zhao, Lin [1 ,2 ,3 ]
Fan, Lei [4 ]
Hu, Guo-Jie [1 ]
Zou, De-Fu [1 ]
Wang, Chong [3 ]
Liu, Shu-Ci [5 ]
Du, Er-Ji [1 ]
Xiao, Yao [1 ]
LI, Ren [1 ]
Liu, Guang-Yue [1 ]
Qiao, Yong-Ping [1 ]
Shi, Jian-Zong [1 ]
机构
[1] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resource, State Key Lab Cryospher Sci, Cryosphere Res Stn Qinghai Tibet Plateau, Lanzhou 730000, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Sch Geog Sci, Nanjing 210044, Peoples R China
[4] Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst Natl Observat & R, Chongqing 400715, Peoples R China
[5] Queensland Govt, Dept Environm & Sci, Brisbane, Qld 4102, Australia
基金
中国国家自然科学基金;
关键词
Ground surface temperature; CMIP6; Cold bias; Permafrost; Qinghai-Tibet engineering corridor; CLIMATE-CHANGE; SOIL-TEMPERATURE; PLATEAU; MODEL; SENSITIVITY; PERFORMANCE; SIMULATION; MOISTURE; DATASET; CHINA;
D O I
10.1016/j.accre.2023.01.007
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Numerous studies were published in the last two decades to evaluate and project the permafrost changes in its thermal state, mainly based on the soil temperature datasets from the Coupled Model Intercomparison Project (CMIP), and discuss the impacts of permafrost changes on regional hydrological, ecological and climatic systems and even carbon cycles. However, limited monitored soil temperature data are available to validate the CMIP outputs, resulting in the over-projection of future permafrost changes in CMIP3 and CMIP5. Moreover, future permafrost changes in CMIP6, particularly over the Qinghai -Tibet Plateau (QTP), where permafrost covers more than 40% of its territory, are still un-known. To address this gap, we evaluated and calibrated the monthly ground surface temperature (GST; 5 cm below the ground surface), which was often used as the upper boundary to simulate and project permafrost changes derived from 19 CMIP6 Earth System Models (ESMs) against in situ measurements over the QTP. We generated the monthly GST series from 1900 to 2014 for five sites based on the linear calibration models and validated them through the three other sites using the same calibration methods. Results showed that all of the ESMs could capture the dynamics of in situ GST with high correlations (r > 0.90). However, large errors were detected with a broad range of centred root-mean-square errors (1.14-4.98 degrees C). The Top 5 model ensembles (MME5) performed better than most individual ESMs and averaged multi-model ensembles (MME19). The calibrated GST performed better than the GST obtained from MME5. Both annual and seasonal GSTs exhibited warming trends with an average annual rate of 0.04 degrees C per decade in the annual GST. The average seasonal warming rate was highest in winter and spring and lowest in summer. This reconstructed GST data series could be used to simulate the long-term permafrost temperature over the QTP.
引用
收藏
页码:85 / 96
页数:12
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